In a typical cellular radio system, mobile terminals (also known as mobile stations and mobile user equipment units (UEs)) communicate via a radio access network (RAN) to one or more core networks. The user equipment units (UEs) can be mobile stations such as mobile telephones (“cellular” telephones) and laptops with mobile termination, and thus can be, for example, portable, pocket, hand-held, computer-included, or car-mounted mobile devices which communicate voice and/or data with the radio access network.
The radio access network (RAN) covers a geographical area which is divided into cell areas, with each cell area being served by a base station, e.g., a radio base station (RBS), which in some networks is also called “NodeB” or “B node”. A cell is a geographical area where radio coverage is provided by the radio base station equipment at a base station site. Each cell is identified by a unique identity within the local radio area, which is broadcast in the cell. The base stations communicate over the air interface (e.g., radio frequencies) with the user equipment units (UE) within range of the base stations. In the radio access network, several base stations are typically connected (e.g., by landlines or microwave) to a radio network controller (RNC). The radio network controller, also sometimes termed a base station controller (BSC), supervises and coordinates various activities of the plural base stations connected thereto. The radio network controllers are typically connected to one or more core networks.
The Universal Mobile Telecommunications System (UMTS) is a third generation or “3G” mobile communication system, which evolved from the Global System for Mobile Communications (GSM), and is intended to provide improved mobile communication services based on Wideband Code Division Multiple Access (WCDMA) technology. UTRAN is essentially a radio access network providing wideband code division multiple access for user equipment units (UEs). The Third Generation Partnership Project (3GPP) has undertaken to evolve further the predecessor technologies, e.g., GSM-based and/or second generation (“2G”) radio access network technologies.
With the adoption of release 6 of the WCDMA standard, a new type of uplink user was introduced. This new user was called an “enhanced” uplink (EUL) user. EUL users are characterized by short (10 or 2 ms) transmit time intervals (TTI), single or multi-code transmission, and potentially large transmit powers. These characteristics enable significantly higher peak data rates than what was achievable previously. Unfortunately, such high-power transmissions significantly increase interference for other uplink users.
One way to address the interference is through the use of a generalized-RAKE (G-RAKE) receiver. RAKE receivers have typically and historically been employed in WCDMA receivers to combat signal fading due to multi-path propagation. Multi-path propagation results from the fact that, in a wireless communication system such as WCDMA, a transmitted signal may travel through multiple propagation paths so that the received signal is a composite of multiple time-shifted versions of the signal. The different time-shifted versions of the signal (e.g., signal images) suffer from different phase and attenuation effects. The multiple time-shifted signal images combine at the receiver in an unpredictable manner, resulting in signal fading.
The goal of the RAKE receiver generally is to detect the individual signal images and combine them coherently. A RAKE receiver typically includes a plurality of correlators, sometimes referred to as fingers, to separately despread different time-shifted signal images, and a combiner to combine the correlator outputs. A delay searcher processes the received signal to identify the delays corresponding to the strongest signal images, and a finger placement processor determines the finger placement based on those delays. The process of finger placement comprises the assignment of a delay to each RAKE finger to align the RAKE finger in time with a signal image.
The G-Rake receiver is an extension of the Rake receiver that is capable of suppressing interference through exploiting the temporal and spatial correlations of an interfering signal. An example generalized RAKE (G-RAKE) receiver is described, e.g., in U.S. Pat. No. 6,363,104, which is incorporated herein by reference. The G-RAKE receiver was proposed to suppress interference in CDMA systems. See, e.g., G. Bottomley, T. Ottosson, Y.-P. B. Wang, “A Generalized RAKE Receiver for Interference Suppression”; IEEE Journal on Selected Areas of Communications, vol. 18, no. 8, pp. 1536-1545, August 2000. Interference suppression is achieved through a set of combining weights that account for correlation between the receiver fingers. The combining weights are given by Expression (1a)w=Ru−1h  Expression (1a)where w is a vector of combining weights, Ru is an impairment covariance matrix (including both interference and noise), and h is a vector of net channel coefficients (the term “net” refers to the combined contribution of the transmit filter, radio channel g, and receive filter). Impairment covariance matrices are described, e.g., in U.S. patent application Ser. No. 11/219,183, entitled “ADAPTIVE TIMING RECOVERY VIA GENERALIZED RAKE RECEPTION”, and United States Patent Publication 2005/0201447/A1, both of which are incorporated herein by reference in their entirety. Parametric computation of an impairment covariance matrix is described, e.g., Cairns et al., Method and apparatus for parameter estimation in a Generalized RAKE receiver, PCT/EP2005/002419, which is incorporated herein by reference in its entirety. The impairment covariance matrix is also used to estimate signal quality, such as SINR, using for exampleSINR=hHRu−1h  Expression (1b)Determining the impairment covariance matrix is typically a prerequisite to generating a proper set of combining weights. It is also a computationally demanding step that must be performed for each uplink user. Thus, the complexity of the G-RAKE solution may exceed the available baseband computation resources as the cell load increases.
Accurate estimation of the impairment covariance matrix used in a G-RAKE or symbol-level weight solution is necessary for maximum performance of the receiver, whether the estimated impairment covariance matrix is used directly (the “non-parametric” G-RAKE solution) or indirectly (for determining scaling parameters of the “parametric G-RAKE solution). The same problem occurs in other equalizer architectures, such as a chip-level or chip equalizer (weights are used in a filter prior to despreading).
As mentioned above, with the introduction of enhanced uplink in 3GPP release 6, a high data rate user within a cell or from other cell may cause significant interference to other uplink users. The parametric G-RAKE solution requires knowledge of channel coefficients for each of the interfering signals to form a model term. Models terms associated with different interferers are weighted and combined with a noise term to formulate estimated impairment covariance. In this way, parametric G-RAKE suppresses an interfering signal that is modeled if it dominates the overall impairment.
In practical implementation, channel coefficients associated with an other-cell interferer might not be available. For example, in the uplink, this may be due to the limitation on the communications between different NodeB's. Even for own-cell interferers, it could be difficult to make their channel coefficients available to the baseband processor of another desired signal if different baseband processor boards are involved. Thus, dominant interference either from other-cell users or other own-cell users makes non-parametric G-RAKE approach favorable.
Generally, the impairment covariance matrix has been estimated using estimated impairment on the limited number of despread pilot symbols in a slot. The limited number of pilot symbols with which to estimate yields substantial estimation error on the resulting covariance matrix. Improvement of this estimation has been accomplished by smoothing multiple estimates together over multiple slots. However, this extension of the estimation window tends to reduce a receiver's ability to track a changing channel as well as follow the burstiness of packet interference power.
Covariance matrix estimation can also be improved through the use of chip samples to estimate data covariance matrix, however this can be undesirably complex and require the conversion from data to impairment covariance.
The prior art does contain examples of using unused codes in blind demodulation. In Kemin Li and Hui Liu, “A new blind receiver for downlink DS-CDMA communications,” IEEE Comm. Letters, July, 1999, unused codes are used to estimate quantities needed to compute blind linear chip equalization weights. One of these quantities R_0, is basically an impairment covariance formed from unused code despread values. However, this covariance is not used with channel estimates to form coherent combining weights. Instead, it is used with a signal covariance to solve for a generalized eigenvector.
The approach in Kemin Li and Hui Liu, “A new blind receiver for downlink DS-CDMA communications,” IEEE Comm. Letters, July, 1999, is extended in D. T. Slock and I. Ghauri, “Blind maximum SINR receiver for the DS-CDMA downlink,” Proceedings of IEEE ICASSP 2000, by adding a constraint to avoid signal cancellation. A variation of this approach is considered in M. Lenardi and D. T. Slock, “A G-RAKE receiver with intracell interference cancellation for a DS-CDMA synchronous downlink with orthogonal codes,” Proceedings of VTC 2000. In M.
Lenardi, A. Medles, and D. T. Slock, “Intercell interference cancellation at a WCDMA Mobile terminal by exploiting excess codes,” Proceedings of VTC 2001 Spring, several structures which use unused codes are considered, in which the received signal is projected onto the unused codes.
What is needed, therefore, and an object of the present invention, are apparatus, method(s), and technique(s) for obtaining accurate estimation of a impairment covariance matrix.